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Found 6 papers, 1 papers with code
Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion Recognition
In this paper, we propose a method for joint modality fusion and graph contrastive learning for multimodal emotion recognition (Joyful), where multimodality fusion, contrastive learning, and emotion recognition are jointly optimized.
Active Learning Based Fine-Tuning Framework for Speech Emotion Recognition
However, existing SER methods ignore the information gap between the pre-training speech recognition task and the downstream SER task, leading to sub-optimal performance.
An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022
In the technical report, we provide our solution for OGB-LSC 2022 Graph Regression Task.
Direct Molecular Conformation Generation
Molecular conformation generation aims to generate three-dimensional coordinates of all the atoms in a molecule and is an important task in bioinformatics and pharmacology.
Improved Drug-target Interaction Prediction with Intermolecular Graph Transformer
The identification of active binding drugs for target proteins (termed as drug-target interaction prediction) is the key challenge in virtual screening, which plays an essential role in drug discovery.
Exploring the Regulatory Function of the N-terminal Domain of SARS-CoV-2 Spike Protein Through Molecular Dynamics Simulation
We performed molecular dynamics simulation on the S protein with a focus on the function of its N-terminal domains (NTDs).
